# -*- coding: utf-8 -*-
import tensorflow as tf
class model_parameter:

    def __init__(self):
        # Network parameters
        self.flags = tf.flags
        #self.flags.DEFINE_string('version', 'istsbp_end_2_end','model version')
        self.flags.DEFINE_string('version', 'init', 'model version')
        self.flags.DEFINE_integer('embedding_word_limit',9999999,'the limit words for embedding')
        self.flags.DEFINE_integer('dal_data_limit', 9999999, 'the limit of dialogue')
        self.flags.DEFINE_integer('input_length', 300, 'the limit of dialogue')

        self.flags.DEFINE_boolean('init_origin_data', False, "Whether init origin data")
        self.flags.DEFINE_string('experiment_name', "TomSun_gen_pic", "the expeiment")
        self.flags.DEFINE_string('cuda_visible_devices', '7', 'Choice which GPU to use')
        self.flags.DEFINE_float('per_process_gpu_memory_fraction', 0.5,
                                'Gpu memory use fraction, 0.0 for allow_growth=True')



    def get_parameter(self,type):

        if type == "load":
            return  self.flags



